Transformer networks have revolutionized NLP representation learning since they were introduced. Though a great effort has been made to explain the representation in transformers, it is widely recognized that our understanding is not sufficient. One important reason is that there lack enough visualization tools for detailed analysis. In this paper, we propose to use dictionary learning to open up these "black boxes" as linear superpositions of transformer factors. Through visualization, we demonstrate the hierarchical semantic structures captured by the transformer factors, e.g., word-level polysemy disambiguation, sentence-level pattern formation, and long-range dependency. While some of these patterns confirm the conventional prior linguistic knowledge, the rest are relatively unexpected, which may provide new insights. We hope this visualization tool can bring further knowledge and a better understanding of how transformer networks work. The code is available at https://github.com/zeyuyun1/TransformerVis

Enterprise Data Modeler needs 2-3 years data analytics, IT experience. Enterprise Data Modeler needs 2-3 years data analytics, IT experience.

Aspirion is an industry-leading provider of complex claims management services. We specialize in Motor Vehicle Accidents, Worker's Compensation, Veterans Administration and Tricare, Complex Denials, Out-of-State Medicaid, and Eligibility and Enrollment Services. Our employees work in an environment that is both challenging and rewarding. Aspirion helps hospitals and other healthcare providers get claims paid correctly by insurance companies, enabling providers to dedicate more resources to patient care and lowering the financial burden on patients. As a tech-enabled services business, Aspirion is investing heavily to embed user-centric design, automation, and machine learning into Compass, our proprietary internal workflow platform supporting the operations of multiple service lines.

Cordarius Cotton, 23, allegedly forgot his 5-month-old son in a bathtub while he left the room to play a video game, resulting in the infant's death, police said. A 5-month-old boy likely drowned in a bathtub this week after his father left the room to play a video game and forgot about the infant, authorities said Tuesday. Cordarius Cotton, 23, told the Jefferson County Sheriff's Office that when he returned about an hour later, the infant was unresponsive. A dispatcher gave CPR instructions over the phone while paramedics were en route, AL.com reported. First responders performed resuscitation efforts on the child as they rushed him to a hospital, but the boy was pronounced dead shortly after arriving.

It was an attention-grabber when TD Bank Group, with U.S. headquarters in Cherry Hill, acquired Toronto-based artificial intelligence company Layer 6 Inc. Yet the move also represents just the latest example of how the banking industry is shedding its stodgy image in a full-blown embrace of technology. Layer 6 uses AI to help analyze data and predict the needs of individual customers, and it's no mystery why TD came calling last month. From answering their questions in a fast yet understandable manner, to sifting through reams of data in order to spot fraud, banks are increasingly using artificial intelligence, a cutting-edge technology once the stuff of science fiction. "Anticipating and meeting customer needs are at the heart of our promise, and we are excited to further accelerate our innovation agenda to deliver well into the future," TD Bank Group CEO Bharat Masrani said.

WIRE)--TSYS (NYSE: TSS), today announced an agreement with Featurespace, a global leader in adaptive behavioral analytics, that will reduce fraud for its clients with a revolutionary machine learning software platform -- the ARICSM engine -- that monitors every individual -- one customer at a time -- to deliver real-time decision capabilities. "TSYS' collaboration with Featurespace aligns with our overall strategy of integrating with advanced, innovative technology partners to help our clients grow their business, reduce costs, and deliver an exceptional customer experience," said Andrew Mathieson, group executive, issuer product group, TSYS. "We will incorporate these capabilities across the credit risk lifecycle, enabling our issuers to catch more fraudulent transactions while dramatically reducing false-positive alerts for genuine transactions -- a sharp contrast to the industry paradigm of blocking more valid transactions in order to detect actual fraudulent activity." The new agreement allows TSYS to strengthen its position in faster payments by leveraging machine learning to provide clients with actionable insights in real time, using adaptive behavioral analytics that result in operational efficiencies. "TSYS has a long-standing leadership position in authorization processing and fraud management and we are excited to integrate our ARIC engine for TSYS' clients," said Martina King, chief executive officer, Featurespace.